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By Ari Banerjee, Senior Vice President, Strategy, Netcracker Technology

Though generative AI (GenAI) is transforming the telecom industry, realizing the full potential of this emerging technology does not come without its challenges. For instance, the proprietary BSS/OSS data needed to create value-based GenAI use cases is protected by privacy laws. Combined with data security concerns, dynamic data sets, the cost to implement large AI foundational models, as well as other challenges, onboarding GenAI isn’t as straightforward as merely flipping a switch.

GenAI Challenges Explained

Like any emerging technology, there are challenges associated with the use of GenAI— this is especially true for the telecom industry. The first and most significant revolves around accessing highly sensitive proprietary telco data without violating privacy laws. Additionally, much of the data required, such as usage and inventory, is dynamic; changing in real time. Since this data isn’t static, it makes it unsuitable for the fine-tuning techniques required to build GenAI models. Additionally, telcos need to ensure that they are protected from security threats made by those using GenAI to infiltrate their systems.

Along with privacy and security concerns, CSPs face other challenges, such as overestimating the technology’s capabilities. To produce content, GenAI uses the data it receives, however large language models (LLMs) such as ChatGPT have no knowledge of the telco business and its processes. Since the input is ambiguous and not tuned to the specifics of the industry, there’s a distinct possibility that GenAI will misinterpret facts and generate inaccurate information.

There’s also the real-time challenge. A significant amount of telco data changes constantly. Usage and inventory data, for example, changes in real time. This makes it unsuitable for fine-tuning techniques that might work with static proprietary data found in other industries.

Lastly, LLMs are not only costly for telcos to build in-house but incur significant running costs across vast compute resources. By some estimates this could cost telcos upwards of USD 700,000 a day, making this investment prohibitive for many.

To overcome these challenges, operators need new approaches to mediate between different types of GenAI models, users and telco data.

Unlocking the Power of GenAI

To make a significant impact, approximately 90% of the industry’s use cases require access to sensitive and proprietary telco data, making integration with BSS/OSS a necessity. To help CSPs overcome challenges and unlock the true power of GenAI, Netcracker recently launched its GenAI Telco Solution.

The GenAI Telco Solution comprises a GenAI Telco Platform consisting of knowledge management to build, test and optimize telco-focused scenarios such as customer care, business operations, sales and network operations. It includes a GenAI Trust Gateway that integrates with the telco IT and data analytics environment, it works in real time to create personalized prompts to ensure high-quality GenAI interactions and it conceals sensitive telco data, providing CSPs with the highest levels of security and accuracy.

This solution securely connects the power of GenAI with telco BSS/OSS data, enabling operators to maximize the value gained from multiple GenAI models and platforms. And, since GenAI models are typically unaware of industry specifics, the GenAI Telco Solution bridges the gap by providing the GenAI model with specific knowledge and data related to the telco business. It educates GenAI models to understand the telecom business by rationalizing interactions through intent recognition, search, retrieval, reasoning and fine-tuning capabilities, improving interaction quality and performance.

By harnessing the power of GenAI in conjunction with BSS/OSS data, operators will benefit in the following ways:

  • Lower costs: GenAI and BSS/OSS will enable CSPs to reduce customer support costs, while improving the quality of customer care. These benefits are derived from improved first-contact resolution, quicker time to resolution and reduced cost per contact. On the network and business operational side, technicians will be able to complete jobs faster. This efficiency will result in operators requiring less technical staff.
  • Improved support of provisioning and troubleshooting: Digital assistants will deliver real-time support for provisioning and maintenance. The technology can also provide troubleshooting assistance for premise-based networks, which can be personalized based on intelligent customer segmentation.
  • Increased revenue: The rapid creation of business ideas such as offers, promotions and discounts, along with the ability to close deals faster, and quickly design and test new services will enable CSPs to improve time-to-value.
  • Improved prediction and optimization: GenAI can produce synthetic data to improve sparse data sets for the model training of predictive maintenance or the detection of unusual calling patterns that could indicate fraudulent activity.
  • Enhanced customer experiences: The data GenAI pulls from the telcos’ BSS/OSS will result in higher net promoter scores, enhanced customer satisfaction and improved customer effort scores.

GenAI is a transformative technology and a great opportunity for telcos. By providing access to their BSS/OSS data and training it on telco-specific business knowledge, they can realize its revolutionary power and reap the benefits.

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